1 Data Description

The data we have chosen for this project is the Australian Road Deaths Database (ARDD) provided by the Australian Bureau of Infrastructure and Transport Research Economics (BITRE). The records are updated monthly from 1986 to 2021. Here is the link to the database : https://data.gov.au/dataset/ds-dga-5b530fb8-526e-4fbf-b0f6-aa24e84e4277/details.

There are two data files. The fatality data contains the demographic and details of people who have died within 30 days of the traffic accident due to injuries caused by an Australia road crash. The fatal crashes data contains the records for the crash, including information like the road type, and speed limit. The two data files can be connected by the crash ID. See Appendix for more detailed descriptions of each variable.

2 Research Questions:

Q1: What demographic has a higher rate of traffic accidents?

Q2: Which road user is more prone to accident with respect to States and over the Years?

Q3: How does the car accident fatality link with the district and accident type?

Q4: Is there any correlation between accidents and holiday? And why are some explanations for the relation(s) or lack thereof.

Q5 :Has accident rate decreased or increased within the past decade (2010- 2020)?

Q6: Possible correlations between number of fatalities and speed limit zone

##   Crash.ID State Month Year Crash.Type Number.Fatalities Bus.Involvement
## 1 20202001   Vic    12 2020   Multiple                 1              No
## 2 20204057    SA    12 2020     Single                 1              No
## 3 20203145   Qld    12 2020     Single                 1              No
## 4 20203208   Qld    12 2020     Single                 1              No
## 5 20203117   Qld    12 2020   Multiple                 2              No
## 6 20201199   NSW    12 2020     Single                 1              No
##   Heavy.Rigid.Truck.Involvement Articulated.Truck.Involvement Speed.Limit
## 1                            No                           Yes         100
## 2                            No                            No         100
## 3                            No                            No          60
## 4                            No                            No         100
## 5                            No                           Yes         100
## 6                            No                            No          50
##   National.LGA.Name.2017 Christmas.Period Easter.Period Time.of.day
## 1           Horsham (RC)              Yes            No       Night
## 2           Tatiara (DC)               No            No         Day
## 3     Sunshine Coast (R)               No            No       Night
## 4          Bundaberg (R)              Yes            No       Night
## 5          Cloncurry (S)              Yes            No         Day
## 6          Upper Lachlan               No            No         Day
##   Crash.ID State Month Year Crash.Type Bus.Involvement
## 1 20203116   Qld    12 2020   Multiple              No
## 2 20201210   NSW    12 2020     Single              No
## 3 20203202   Qld    12 2020     Single              No
## 4 20201093   NSW    12 2020     Single              No
## 5 20203161   Qld    12 2020   Multiple              No
## 6 20203179   Qld    12 2020   Multiple              No
##   Heavy.Rigid.Truck.Involvement Articulated.Truck.Involvement Speed.Limit
## 1                            No                            No          60
## 2                            No                            No         100
## 3                            No                            No         100
## 4                            No                            No         100
## 5                            No                            No          70
## 6                            No                            No         100
##          Road.User Gender Age National.LGA.Name.2017 Christmas.Period
## 1 Motorcycle rider   Male  28             Cairns (R)               No
## 2        Passenger   Male  89                 Walcha              Yes
## 3           Driver   Male  21    Charters Towers (R)              Yes
## 4           Driver   Male  81                 Walcha               No
## 5           Driver Female  66        Moreton Bay (R)               No
## 6        Passenger   Male  79     Lockyer Valley (R)               No
##   Easter.Period   Age.Group Time.of.day
## 1            No    26_to_39       Night
## 2            No 75_or_older         Day
## 3            No    17_to_25         Day
## 4            No 75_or_older       Night
## 5            No    65_to_74       Night
## 6            No 75_or_older         Day

3 Data Analysis

3.1 Q. What demographic has a higher rate of road accidents or fatal crashes?

  • sex as a factor in accident
  • Age as a factor in accident
Australian road deaths database and fatal crashes, by age and gender

Figure 3.1: Australian road deaths database and fatal crashes, by age and gender

3.1.1 Analysis

  • The Australian Road Deaths Database provides basic details of road transport crash fatalities in Australia as reported by the police each month to the State and Territory road safety authorities.
  • Road deaths from recent months are preliminary and the series is subject to revision.
  • The above graph 3.1 explains, what demographic has a higher rate of traffic accidents considering Age.Group and Gender as a factor.
  • The age group between 40 to 64 in both the genders, had the maximum risk of fatal crash involvements compared to the rest of the age groups.
  • Male drivers compared to Female for the same age group have the highest rate of road accidents i.e. more than 3000 fatal crashes. Hence, Male drivers between age group 40 t0 64 are more susceptible to the fatal crash involvement.

3.2 Q. Which road user is more prone to accident with the States and over the Year?

With respect to Year
Australian road deaths database and fatal crashes, by age and gender

Figure 3.2: Australian road deaths database and fatal crashes, by age and gender

3.2.1 Analysis

  • This analysis is with respect to the vulnerable Road Users who are prone to road accidents over the years in Australia.
  • According the above graph 3.2, Driver is one of the most vulnerable road user prone to accident through-out the years.
  • In 2010 and 2016 driver experienced the peak where there were maximum number of casualties.
  • Along with that even Pedestrian, Passenger and Motorcycle rider are among the second most vulnerable road user, prone to accident.
  • The number of casualties for Motorcycle rider and Pedestrian has mostly been constant through-out the years from 2010 till 2020
  • The casualties for Passenger shows a slight decrease over the years.

we group the data by states and the type of Road Users which have involved in the fatal accidents.

Number of Fatal Accidents with Different Road User in Different State

Figure 3.3: Number of Fatal Accidents with Different Road User in Different State

3.2.2 Analysis

From the graph above 3.3:

In all the states

  • more than half of the total fatal accidents with drivers involved.
  • Accidents with Passenger involved account for the second large portion of the total accidents
  • follow by motorcycle rider and then pedestrian involved accidents.

Interpretation:

  • Most fatal accidents with the drivers and passengers involved. relatively less pedestrian involved in fatal car accidents. We may interpret that most of the people drive in Australia, that is the reason more drivers and passenger involved in fatal car accidents. Another interpretation is most of the car accidents happened in highway or it is a crashed between cars or crashed between car and the road.

3.4 Is there any correlation between accidents and holiday? And why are some explanations for the relation(s) or lack thereof.

## [1] 12  4  1  3

3.4.1 Analysis

  • The month shows that the Christmas period is in December and January. And the Easter period is in March and April.

Figure 3.4: The fatal crashes happen in Christmas period from 2018 to 2020

3.4.2 Analysis

It can be seen from 3.4 that :

  • The number of crashes increases in VIC, WA and NSW in 2018 and 2019 respectively during Christmas period.

  • The OLD got a sudden decline in Christmas period of 2020, maybe due to the effectof COVID virus.

  • For other states, the crashes either fluctuated or drop. Therefore, there is no dominate correlation between crashes and Christmas.

Figure 3.5: The crashes in Easter period from 2018 to 2020

3.4.3 Analysis

In Figure 3.5, in 2018, only WA has a slightly increase in Easter period. For Victoria, the number of crashes drops dramatically in March to April of 2018 and 2020. While other states fluctuate in these period. There is no clear correlation between cashes in Easter period in different states.

Figure 3.6: Fatal crashes happens by day and night

3.4.4 Analysis

The Figure 3.6 compares the fatal crashes that happen in days and night. + Obviously, there are more crashes happen on the days than night.

  • In 2018 and 2013, the crashes of ACT happen more on night rather than day.

  • In NT, some crashes happens more at night than day in 2020, 2018, 2015.

3.5 Q. Has accident rate decreased or increased within the past decade (2010- 2020)?

3.5.1 Analysis

Although 2019 was the year the pandemic started, it surprisingly was not the year with the lowest number of fatal crashes in total.

3.6 Q. Possible correlations between number of fatalities and speed limit zone

Table 3.1: Yearly number of fatal crashes by speed limit (km/h)
Year <= 40 50 60 70-90 >= 100
2010 7 116 236 283 588
2011 18 147 181 239 554
2012 21 132 248 277 499
2013 16 131 202 251 492
2014 18 111 192 229 490
2015 20 113 222 249 487
2016 17 132 215 290 536
2017 35 152 202 241 487
2018 18 131 192 228 477
2019 21 129 185 241 515
2020 18 126 171 234 452

3.6.1 Analysis

The speed limits are split into 5 respective parts which is 40 and below, 50, 60, 70-90 and 100 and above, all measured in kilometer per hour (km/h). Areas which have less than 40 km/h are often shared zones, school zones and places with high density of pedestrian. 50 km/h are default speed limit within built up areas in every state in Australia except for Northern Territory. 60 km/h are sub-arterial roads, as well as the default speed within built up area in Northern Territory. 70-90 are connector and small highways. 100 and above area highways speed limits.

Between 2010 and 2020, table 3.1 showed that the overall trend in fatal crashes is reduced for speed limit zones outside built-up areas but increased for zones within built-up areas. However, within the period of 2015-2016, all zones see an increase in number of fatal crashes. The number of fatal crashes reduced or increased in varying number as well as rate across the speed zones. With the speed zones of 100 and above and 60 km/h decreased by largest proportion, about 25%.

Comparing proportion of yearly fatal crash by speed limit

Figure 3.7: Comparing proportion of yearly fatal crash by speed limit

3.6.2 Analysis

One notable point as figure 3.7 showed is throughout the period analyzed, not only is the speed zone of 100 km/h and above has highest percentage of fatal crash, but it accounts for nearly 50% of all fatal crashes in Australia. While 50 km/h and below speed zones account for less than 10% of all fatal crashes. It is generally well known that the higher the speed a vehicle is traveling at, the longer the stopping distance is, and thus fatal crash is more likely to occur on highways. Kloeden, Woolley & McLean (2007) found that following the reduction of urban speed limit from 60 to 50 km/h in South Australia in 2003, there was a 23% reduction in fatal crashes in 50 km/h zones and 16% reduction in 60 km/h zones.

Comparing number of fatalities and fatal crashes by speed zone

Figure 3.8: Comparing number of fatalities and fatal crashes by speed zone

Percentage difference between fatalities and fatal crashes

Figure 3.9: Percentage difference between fatalities and fatal crashes

3.6.3 Analysis

Figure 3.8 illustrated that not only the number of fatal crashes increased with speed limits, but number of fatalities increased as well, and in higher proportion than the increase of crashes. The difference between number of fatalities and number of crashes are made clearer in figure 3.9. The percentage difference is similar in speed zones of 60 km/h and below, at around 3%. However, the difference for 70-90 km/h is approx. 8% and for highway speed is nearly 13%.

3.6.4 Citations

Kloeden, C., Woolley, J., & McLean, A. J. (2007, October). A follow-up evaluation of the 50km/h default urban speed limit in South Australia. In Proceedings of.